# Investigating Anatomic Orientations of Brain Degeneration in Alzheimers Disease

> **NIH NIH R03** · WAKE FOREST UNIVERSITY HEALTH SCIENCES · 2020 · $151,286

## Abstract

PROJECT SUMMARY
Alzheimer's disease (AD) is the
brain
to
intervention To slow the progression of
AD through intervention, a non-invasive and expensive early detection method is key. Using magnetic
resonance imaging (MRI) to detect very small anatomic changes in the brain could play an important role in
most common form of dementia. The disease is associated with changes in
 structures that support memory and higher cognitive functions. The pathophysiologic processes leading
AD begin well before the onset of clinically detectable symptoms. Currently, no medication or particular
has been clearly shown to delay or halt the progression of the disease.
early detection. The proposed multidisciplinary research project will involve the collaboration of investigators
from diverse and complementary backgrounds (abiomechanical engineer, an MR physicist, a neuroradiologist
and
cognitive
neuroscientists)
to investigate early AD imaging biomarkers which can be derived from one of
the most common structural MRI scans. We
structural
MRI
biomarkers
derived
from
propose two specific
biomechanical methods to
aims to validate
measure signs
the
feasibility
of
early
AD.
of new
Aim 1:
Considering anatomic features of individual brains, such as orientations of cortical sulci and gyri, we will
analyze three-dimensional deformations along these neuroanatomic orientations. Using the Alzheimer's
Disease Neuroimaging (ADNI) dataset, we will compare the longitudinal
changes
impairment),
Initiative
in brains of 301 cognitively normal individuals and 870
using images that were obtained over a 48-month period.
people
with
trajectory of
early AD (mild
anatomic
cognitive
We will compare the statistical power to
detect abnormal brain degeneration patterns in early AD subjects between our new morphometry algorithm
and conventional volumetric or cortical thickness measures. Aim
predict
and
(PET)
biomarkers.
longitudinal
biomarkers
multidisciplinary
advance
2: We will propose a statistical model to
individual cognitive decline, considering substantial inter-subject variability in baseline characteristics
disease progression rates. Within the ADNI dataset, we will use longitudinal positron emission tomography
images and MRI biomarkers, to determine the temporal ordering among MRI, PET, and cognitive
The goal of these studies is to gauge the clinical utility of imaging biomarkers by correlating with
neurop sychological assessment data. Here, we will determine if single or multi-modality imaging
can predict decline clinical onset. The large datasets available and the
team led by an Early-Stage Investigator will facilitate the likelihood of meaningful results to
the field of AD diagnosis and prevention
cognitive before
. This framework will be the foundation of continued work to
create a new paradigm for use structural MRI biomarkers in longitudinal studies of AD. Once developed, our
software programs will be shared through a public software development/sharing platform.

## Key facts

- **NIH application ID:** 10017843
- **Project number:** 5R03AG063299-02
- **Recipient organization:** WAKE FOREST UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Jeongchul Kim
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $151,286
- **Award type:** 5
- **Project period:** 2019-09-15 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10017843

## Citation

> US National Institutes of Health, RePORTER application 10017843, Investigating Anatomic Orientations of Brain Degeneration in Alzheimers Disease (5R03AG063299-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10017843. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*